Prognostic and incremental value of computed tomography-based radiomics from tumor and nodal regions in esophageal squamous cell carcinoma

Objective This study aimed to evaluate the prognostic value of preoperative radiomics and establish an integrated model for esophageal squamous cell cancer (ESCC). Methods A total of 931 patients were retrospectively enrolled in this study (training cohort, n=624; validation cohort, n=307). Radiomics features were obtained by contrast-enhanced computed tomography (CT) before esophagectomy. A radiomics index was set based on features of tumor and reginal lymph nodes by using the least absolute shrinkage and selection operator (LASSO) Cox regression. Prognostic nomogram was built based on radiomics index and other independent risk factors. The prognostic value was assessed by using Harrell’s concordance index, time-dependent receiver operating characteristics and Kaplan-Meier curves. Results Twelve radiomic features from tumor and lymph node regions were identified to build a radiomics index, which was significantly associated with overall survival (OS) in both training cohort and validation cohort. The radiomics index was highly correlated with clinical tumor-node-metastasis (cTNM) and pathologic TNM (pTNM) stages, but it demonstrated a better prognostic value compared with cTNM stage and was almost comparable with pTNM stage. Multivariable Cox regression showed that the radiomics index was an independent prognostic factor. An integrated model was constructed based on gender, preoperative serum sodium concentration, pTNM and the radiomics index for clinical usefulness. The integrated model demonstrated discriminatory ability better compared with the traditional clinical-pathologic model and pTNM alone, indicating incremental value for prognosis. Conclusions CT-based radiomics for primary tumor and reginal lymph nodes was sufficient in predicting OS for patients with ESCC. The integrated model demonstrated incremental value for prognosis and was robust for clinical applications.